the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Jul 2026
Enhanced production and methylation of bacterial branched tetraether lipids responding to water content-mediated redox changes in Tibetan Plateau permafrost soils
Abstract. Branched glycerol dialkyl glycerol tetraethers (branched GDGTs) are bacterial membrane lipids widely used as biomarkers for terrestrial and marine paleoenvironmental reconstruction. Sparsely branched and overly branched GDGTs (sb- and ob-GDGTs) are predominantly detected in anaerobic environments and have been proposed as redox proxies in marine settings. However, their distributions, environmental controls, and biological sources in terrestrial environments remain poorly understood. Here, we investigated the distributions of sb/br/ob-GDGTs, together with bacterial community composition in two permafrost peatland soil profiles from the Tibetan Plateau. Our results demonstrate that elevated soil water content (SWC) influences branched GDGT composition by creating anaerobic conditions that promote the production and methylation of sb/br/ob-GDGTs. Co-occurrence network analyses revealed strong positive correlations between the relative abundances of sb/br/ob-GDGTs and anaerobic bacterial communities, including taxa affiliated with Proteobacteria, Caldithrix, Nitrospirae, Spirochaetes and Chloroflexi. These findings suggest that oxygen-limited conditions may reshape sb/br/ob-GDGT-producing bacterial communities in permafrost soils, thereby promoting the accumulation of sb/br/ob-GDGTs. Furthermore, we demonstrate that the methylation index of ob- and br-GDGTs (MIob/br) serves as a sensitive indicator for soil redox dynamics and may be applied to reconstruct paleohydrological variability, thereby aiding assessments of permafrost carbon-cycle feedbacks to climate warming.
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- RC1: 'Comment on egusphere-2026-3837', Fatemeh Ajallooeian, 01 Sep 2026 reply
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Review of Enhanced production and methylation of bacterial branched tetraether lipids responding to water content-mediated redox changes in Tibetan Plateau permafrost soils
5 Wan Zhang1, #, Xiaotong Tang2, 6, #, Wenyong Yao1, Jing Qian3, Wei He1, Yanhong
6 Zheng2, Yuanqing Zhu1, 4, Ronnakrit Rattanasriampaipong5, Yufei Chen1, 9, Fengfeng
7 Zheng1, 7, Chuanlun Zhang1, 8
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By Fatemeh Ajallooeian, 30/08/2026
General comment:
Genuinely one of the better manuscripts I've reviewed in a while. The dataset is thorough, pairing lipid biomarkers with16S sequencing and functional gene searches gives real weight to the microbial source interpretations rather than leaving them speculative. Writing is careful throughout, and the authors are upfront about where the evidence is solid vs where they're extrapolating, the Halamka discussion and the Gmm homolog caveat in 4.2 are good examples. Analysis is rigorous, and most of my pushback is just asking for caveats they clearly already know about to be stated more explicitly, not real problems with the approach. Figures are clear and well built, the ternary plot and MI comparisons in Fig. 5 put this dataset nicely in context against marine systems. Overall a genuinely novel contribution to a real gap in the terrestrial GDGT literature, just needs a handful of minor clarifications before it's ready.Â
Detailed comments:
Introduction:
Lines 88-99: the ob/sb-GDGT and O2 depletion relationship is drawn from marine studies and then applied to the permafrost soil context without acknowledging that this is an extrapolation. Marine water column/sediment redox chemistry differs considerably from soil redox. As currently written, the mechanism reads as already established, when in fact its transferability to terrestrial systems is arguably what this study is testing. I'd recommend adding a sentence explicitly noting that this link has not previously been demonstrated outside marine settings.
The rationale for combining lipid MS with 16S sequencing is also not made explicit throughout the introduction. I agree as the authors themselves note too that Acidobacteria alone don't account for the full range of known brGDGT producers, this is the natural justification for the 16S component, but it should be stated directly rather than left implicit in my opinion. A 1-2 sentence statement clearly mentioning this should suffice.
Lines 100-110: this paragraph builds a chain on why there are proxy complications for application of brGDGTs in permafrost, but then it shifts to ob/sb-GDGTs specifically, it is somewhat unclear whether you’re claiming brGDGT proxies are unreliable in saturated soils or ob/sb GDGTs are the opportunity for a new proxy here? Or both? I would try to reframe and tie this together.
Methods:
Cores were collected in a single field season (July-Aug 2018). Since the whole premise here is that SWC-driven redox variation shapes lipid distributions, one summer snapshot can't really tell a stable moisture/redox gradient apart from seasonal or year to year variability. This doesn't need fixing, but should be flagged as a limitation in my opinion.
Lines 227-230: ASV-level networks use r-value >0.7 and genus-level use r-value >0.6, but then line 230 says genera were selected for BLAST using r-value > 0.7, I would clear this up t oavoic confusion.
Results:
Line 318-322: The Methanobacteria/(Methanobacteria+Thaumarchaeota) ratio is framed as "more direct evidence" of redox conditions, but it only accounts for two of the anaerobic archaeal groups you've already brought into the discussion, Bathyarchaeota are mentioned two sentences earlier as another GDGT-0-producing anaerobic lineage in watersaturated soils, but aren't included in this ratio. Is there a reason for it? If Bathyarchaeota make up a meaningful share of the archaeal community at either site, leaving them out could skew how an anaerobic dominant ratio makes a sample look.
Line 336-344: The text splits genus-level nodes into anaerobic (13.51%) and aerobic (33.78%), but that only accounts for about half the network (as seen on Fig. 3c's legend shows a third "unknown" category)), which based on the numbers makes up roughly 53% of the 74 genera shown, and it's not discussed at all in the text. I suggest adding a line acknowledging this "unknown" group, since as written a reader could assume aerobic/anaerobic is the dominant split when actually it's closer to half.
Discussion:
Lines 408-411: I'd elaborate a bit here on how the Halamka et al. (2021) evidence is being used, since the logic connecting the two culture based observations isn't fully explained. Authors first say Acidobacteria grown aerobically are brGDGT sources referencing Chen et al., and Halamka et al, then say oxygen limitation may stimulate brGDGT production "in certain strains". Are these the same strains showing both behaviors (I think Halamka et al does explain this fully in their paper, but it’s best to not assume reader knows that and fully give the context). The next sentence then jumps from oxygen limitation in certain strains to “facilitate the anaerobic production of brGDGTs", which goes further than oxygen limited toward fully anaerobic, and it's not clear the cited evidence supports that jump. Since this paragraph is doing a lot of the work bridging the aerobic culture evidence to your anaerobic hypothesis, worth tightening up exactly what Halamka et al. (2021) showed.
 Fig. 4: a couple of issues here, firstly the panels aren't labeled, are they combined dataset for both sites? or is each panel representing a different site? Secondly regarding the Lü et al. (2019) reference data, in the overlap range (SWC 0–50%), the grey points don't really track the same trend as your own data from what I observe, so it's worth a line addressing that, and clarifying whether Lü et al. was included in the R2 calculation at all.
Lines 461-472: authors say the Gmm homolog's role in bacteria "has not yet been experimentally verified," which is fair and cautious. But two sentences later, that same unverified homology is used to say marine bacteria "may possess a greater capacity for producing highly methylated brGDGTs... probably gmm gene homologs" so you're building a fairly specific story on a mechanism you just said isn't confirmed to even work in bacteria. The wording used ("we infer," "may," "probably") is cautious, I agree it’s not really overclaiming, but I would be more careful in taking a mechanism from a different domain (archaea) and applying it provisionally to bacteria without testing it directly.
Figure 5: I think in the wetland sediments panel (orange datapoints, "ns" for not significant) is the same dataset from Lu et al. (2019) that shows up as the grey points in Fig. 4? Right? where the trend also didn't really hold in the 0-50% SWC overlap zone. So the claim that MI ob/br tracks SWC "particularly when SWC exceeded 50%" doesn't actually hold for the dataset sitting right next to permafrost soil in the same panel in my opinion, and this isn't mentioned anywhere. I agree that wetland sediments are the closest analog you have to permafrost out of the four datasets, so I think this needs addressing directly, is the SWC-MI relationship something specific to permafrost, or is something else going on with the Lu dataset? Also, same panel is mixing two different kinds of comparison. Mariana trench and water column are split by actual measured oxic/anoxic conditions, but wetland sediments and permafrost soil are split by low and high SWC as a proxy for redox state. Â Then line 451 reads "MI ob/br index is significantly higher in anoxic environments than in oxic environments" as a blanket statement for the whole figure, but for two of the four datasets "anoxic" is really just inferred from SWC, not measured. I would clarify this so the significance stars don't all read as the same kind of comparison.
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